Fundamentals of Causal Inference: With R

ISBN-13: 9780367705053 / Angielski / Twarda / 2021 / 236 str.

Babette A. Brumback

Opis

Explains and relates different methods of confounding adjustment in terms of potential outcomes and graphical models, including standardization, difference-in-differences estimation, the front-door method, instrumental variables estimation, and propensity score methods.

Spis treści

1. Introduction. 2. Conditional Probability and Expectation. 3. Potential Outcomes and the Fundamental Problem of Causal Inference. 4. Effect-measure Modification and Causal Interaction. 5. Causal Directed Acyclic Graphs. 6. Adjusting for Confounding: Back-door method via Standardization. 7. Adjusting for Confounding: Difference-in-Differences Estimators. 8. Adjusting for Confounding: Front-door method. 9. Adjusting for Confounding: Instrumental Variables. 10. Adjusting for Confounding: Propensity-score Methods. 11. Efficiency with Precision Variables. 12. Mediation.

O autorze

Babette A. Brumback is Professor and Associate Chair for Education in the Department of Biostatistics at the University of Florida; she won the department’s Outstanding Teacher Award for 2020-2021. A Fellow of the American Statistical Association, she has researched and applied methods for causal inference since 1998, specializing in methods for time-dependent confounding, complex survey samples and clustered data.